Volume 13, Issue 1, March – April 2012; Article-016
ISSN 0976 – 044X
Research Article
ADMET & MOLECULAR DOCKING STUDIES OF NOVEL ZANAMIVIR ANALOGS AS
NEURAMINIDASE INHIBITORS
1
2
3
4
Manoj Kumar Mahto *, V Likhitha Raj , Prof. M. Bhaskar , Divya.R
Dept. of Bioinformatics (Biotechnology), Acharya Nagarjuna University, Guntur, AP, India.
2
Dept. of Pharmaceutical Chemistry, Bharat Institute of Pharmacy, Ibrahimpatnam, AP, India.
3
Dept. of Zoology, Sri Venkateswara University, Tirupati, AP, India.
4
Dept. of Bioinformatics, Gulbarga University, Karnataka, India.
*Corresponding author’s E-mail: manoj4bi@gmail.com
1
Accepted on: 29-12-2011; Finalized on: 25-02-2012.
ABSTRACT
Now days, Influenza is one of the highly potent contagious pathogen spreading and threatening all over the world by causing
dreadful respiratory diseases like Swine flu for which enzyme Neuraminidase (NA) is the major drug target. Neuraminidase,
otherwise called as sialidases, exists as a mushroom shape projection on the surface; catalyze the hydrolysis of terminal sialic acid
residues from the newly formed virions and from the host cell receptors. Reports of the recent studies reveal that enzyme
neuraminidase is resistant to drugs like Oseltamivir. In the present study, we have used commercial computational tools like
Accelry’s Discovery Studio 2.5 to identify the novel analogs that established better binding than the Zanamivir. From the docking
studies, we found that substitution of hydroxyl group with methyl is having better dock score and higher interaction energy than
Zanamivir.
Keywords: Influenza, H1N1, Neuraminidase, Zanamivir, ADMET, Molecular docking.
INTRODUCTION
Influenza, commonly referred to as the flu, is an
infectious disease caused by RNA viruses of the family
Orthomyxoviridae (the influenza viruses), that affects
birds and mammals. Influenza spreads around the world
in seasonal epidemics, resulting in the deaths of between
250,000 and 500,000 people every year, and millions in
pandemic years1. The impact of Influenza is felt globally
each year when the disease develops in approximately 20
percent of the world’s population. Although vaccination is
the primary strategy for the prevention of influenza,
there are number of likely scenario for which vaccination
is inadequate and effective antiviral agents would be of
utmost importance. In the course of pandemic, vaccine
supplies would be inadequate. Antiviral agents thus form
an important part of a rational approach to epidemic
influenza and are critical to planning for a pandemic2.
The two classes of antiviral drugs used against influenza
are neuraminidase inhibitors and M2 protein inhibitors
(adamantane derivatives). Neuraminidase inhibitors are
currently preferred for flu virus infections since they are
3
less toxic and more effective .
The antiviral drugs amantadine and rimantadine block a
viral ion channel (M2 protein) and prevent the virus from
4
infecting cells . These drugs are sometimes effective
against influenza A if given early in the infection but are
always ineffective against influenza B because B viruses
do not possess M2 molecules.
Neuraminidase (NA or N) is a glycoprotein, which is found
as projections on the surface of the virus. It forms a
tetrameric structure with an average molecular weight of
220,000. The NA molecule presents its main part at the
outer surface of the cell, spans the lipid layer, and has a
small cytoplasmic tail5. NA acts as an enzyme, cleaving
sialic acid from the Haemaglutin (HA) molecule, from
other NA molecules and from glycoproteins and
glycolipids at the cell surface. Hence it is also known as
sialidase. It also serves as an important antigenic site, and
in addition, seems to be necessary for the penetration of
the virus through the mucin layer of the respiratory
epithelium6.
In the present study, we have designed 9 novel Zanamivir
analogs, performed docking studies using CDocker of
Accelry’s Discovery Studio 2.5 and identified 7 ligands
that established better binding affinity towards the
enzyme neuraminidase than Zanamivir. Also, we
evaluated these analogues for predicted ADME and
Toxicity studies.
MATERIALS AND METHODS
Ligand & Protein Selection: The enzyme Neuraminidase
was retrieved from the RSCB PDB website
(http://www.pdb.org) with PDB ID: 3B7E7. Protein
retrieved from the database is in complex with Zanamivir
which is useful in identification of its active binding sites.
Active binding sites were identified by using an online
tool, PoseView (www.poseview.de/poseview/wizard)
given in Fig:1, and also verified by using graphic interface
of Accelry’s Discovery Studio 2.5
Analogs of Zanamivir, a Neuraminidase inhibitor were
drawn by selecting Zanamivir as Lead moiety and altering
its carboxylic acid groups using Accelry’s Symyx Draw 4.0
according to the Lipinski’s rule. Zanamivir analogs were
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Volume 13, Issue 1, March – April 2012; Article-016
ISSN 0976 – 044X
listed in Table: 1 and modifications of Zanamivir structure
were shown in Fig:2.
Descriptors protocol of the Discovery studio 2.5 in which
we predicted the levels for Blood-Brain-Barrier (BBB)
penetration10, Intestinal Absorption11, Aq. Solubility12,
13
14
Hepatotoxicity , Cytochrome P450 inhibition , and
15
Plasma Protein Binding (PPB) levels .
Toxicity profiles of the analogs were studied by using
“toxicity prediction-Extensible” protocol of Discovery
Studio 2.5 which follows Bayesian Model16. Toxicity
profiles like Aerobic Biodegradability, AMES mutagenisity,
Developmental Toxicity Potential, ocular and Skin
irritancy, and carcinogenicity using various animal models
(In silico) were predicted.
Figure 1: Identification of the active binding site of the
protein enzyme Neuraminidase (PDB ID: 3B7E) using
Poseview tool
Molecular Docking: Protein – ligand interactions between
Zanamivir, its analogs and Neuraminidase enzyme were
identified by using CDOCKER docking protocol of
Discovery Studio 2.5. CDOCKER is a molecular dynamics
(MD) simulated-annealing-based algorithm. The ligand
side chains are conformationally sampled and are
subjected to core-constrained protein docking, using a
modified CHARMm-based CDOCKER method to generate
top poses along with CDOCKER energies17-19.
RESULTS AND DISCUSSION
Figure 2: Modifications of the Zanamivir structure.
Table 1: Substituted functional groups of newly designed
Zanamivir analogs
Ligand
No
1
2
3
4
5
6
7
8
9
Ligand Name
R1
R2
R3
R5
R6
ZANAMIVIR
ZANAMIVIRIR ETHYL
Z. HYDROXY
REPLACES METHYL
Z.ISOPROPYL
Z.METHYL
Z.PYRAN ALPHA
METHYL
Z.PYRAN BETA
METHYL
Z.METHYL 2
Z.PYRIDINE
Z.THIOL
O
O
OH
ETHYL
H
H
H
H
OH
OH
O
OH
H
H
METHYL
O
O
ISOPROPYL
METHYL
O
OH
O
OH
O
N
S
OH
OH
OH
H
H
H
H
ALPHA
H
METHYL
BETA
H
METHYL
H
METHYL
H
H
H
H
OH
OH
OH
OH
OH
OH
OH
Processing of Target Protein: Internal ligands and the
crystallographic water molecules were removed from the
protein and missing Hydrogen’s was added8.
Crystallographic disorders and unfilled valances were
corrected.
Geometrical
optimization/
energy
minimization of the protein was performed by employing
CHARMm27 force field and RMSD of 0.01 using Discovery
9
Studio’s proprietary algorithm, Smart Minimizer .
Ligand Preparation: Ligands were designed and
geometrically optimized by using the “Smart Minimizer”
minimization algorithm of Discovery Studio 2.5 by
employing CHARMm27 Force field with RMSD of 0.0001.
ADME & Toxicity Profiles: For all the newly designed
ligands, ADME properties were studied by using ADME
Enzyme Neuraminidase with PDB ID: 3B7E retrieved from
PDB website is geometrically optimized and screened for
its active binding sites. Zanamivir analogs were designed
according to Lipinski’s Rule of Five and geometrically
optimized to their least energy – high stability state and
their molecular properties like, Molecular wt.(MW),
surface area, volume, AlogP are listed in the Table: 2.
Optimized ligands are used for the ADMET studies and
also for Molecular Docking studies along with the
optimized protein.
Table 2: Molecular properties of novel Zanamivir analogs
Mol
No of HB No of HB
Mol MW Surface Volume
donors acceptor
Area
Zanamivir 332.31 333.81 200.99
8
8
1
360.363 368.32 227.75
7
8
2
330.337 337.78 209.91
7
7
3
374.39 385.34 242.84
7
8
4
346.336 353.05 211.97
7
8
5
343.336 353.23 216.08
8
8
6
346.336 353.23 216.08
8
8
7
346.336 350.78 218.49
8
8
8
331.325 333.81 203.05
9
8
9
348.375 344.92 212.07
8
8
Ligand
No
AlogP
-3.395
-2.821
-1.983
-2.443
-3.17
-2.949
-2.949
-3.018
-3.848
-2.837
ADME & Toxicity Studies: ADME (Absorption,
Distribution, Metabolism and Excretion) profile, also
called as pharmacokinetic profile of Zanamivir and its
analogs are tabulated in the Table: 3. All the ligands have
optimum Aq. Solubility and better drug like properties
without BBB penetration, thus chances of causing CNS
effects are marginal. All the analogs are Cytochrome P450
enzyme non-inhibitors. All the ligands show low intestinal
absorption and the plasma-protein binding are less than
90%. Dose dependent hepatotoxicity is found for the
ligands 2, 3, 5, and 6.
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Table 3: ADME profiles of the Zanamivir analogs
Ligand NO
Zanamivir
1
2
3
4
5
6
7
8
9
BBB level
4
4
4
4
4
4
4
4
4
4
Absorption level
3
3
3
3
3
3
3
3
3
3
Solubility level
4
4
4
4
4
4
4
4
5
4
Hepatotoxicity level
0
1
0
1
0
1
1
0
0
0
CYP2D6 level
0
0
0
0
0
0
0
0
0
0
PPB level
0
0
0
0
0
0
0
0
0
0
Table 4: Toxicity profile of the novel Zanamivir analogs obtained by using Toxicity prediction tool of Discovery studio 2.5
Ligand
Zanamivir
1
2
3
4
5
6
7
8
9
Carcinogenicity
Aerobic
AMES
Developmental
Ocular
Skin
Female Male Female
Bio-Degradailability Mutagenicity Toxicity Potential Irritancy Irritancy Rodent
Mouse Mouse
Rat
YES
NO
YES
YES
NO
NO
NO
NO
NO
YES
NO
YES
YES
YES
NO
NO
NO
NO
YES
NO
YES
YES
YES
NO
NO
NO
NO
YES
NO
YES
NO
YES
NO
NO
NO
NO
YES
NO
YES
YES
YES
NO
NO
NO
NO
YES
NO
YES
YES
NO
NO
NO
NO
NO
YES
NO
YES
YES
NO
NO
NO
NO
NO
YES
NO
YES
YES
YES
NO
NO
NO
NO
YES
NO
YES
YES
NO
NO
NO
NO
NO
YES
NO
YES
YES
NO
NO
NO
NO
NO
From the In silico toxicity studies, listed in Table: 4, we
found that none of the analogs were exhibited
carcinogenic and mutagenic potentials. All the ligands
including Zanamivir have dose dependent toxicity
potential and all are biodegradable in aerobic conditions.
Except isopropyl derivative of the Zanamivir (ligand 3),
remaining all other analogs are ocular irritants. Ligands 1,
2, 3, 4, and 7 show irritancy towards skin. As, these drugs
are not useful as topical or ocular formulations, irritant
nature of these ligands can be excluded.
Table 5: Docking score and interaction energies of the
ligands with the protein 3B7E
Ligand No Cdocker Score Interaction Energy
Zanamivir
16.585
34.000
1
18.42
22.1808
2
29.311
43.0667
3
19.47
41.32
4
25.5624
38.5017
5
9.19
30.6308
6
10.5105
34.02
7
27.5626
48.203
8
21.5083
24.16
9
24.16
41.544
Molecular Docking: Protein – ligand interactions were
identified by using CDOCKER docking protocol of Accelry’s
Discovery Studio 2.5. From the docking result listed in
Table: 5 we found that Zanamivir has docking score of
16.585 with interaction energy of 34.00. Only pyran alpha
and beta methyl substituted analogs (ligands 5, 6) are
having lesser dock score when compared to Zanamivir.
Methyl substituted analogs (ligand 2 and 7) have highest
dock scores of 29.311 and 27.56 respectively. Out of 9
Male
Rat
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
analogs, 7 have better dock score than Zanamivir. Ligand
2 has 4 hydrogen bonds with the receptor residues like
ARG 118, 371, TYR 406 and ASP 151 which can be
visualized in the fig: 3. Binding site pocket of the docked
protein can be visualized in the fig:4 along with ligand 2.
Figure 3: Binding interaction of Ligand 2 with enzyme
Neuraminidase protein
Figure 4: Binding site pocket of the protein 3B7E along
with its docked ligand 2
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Volume 13, Issue 1, March – April 2012; Article-016
ISSN 0976 – 044X
(HCV) using molecular docking studies, Journal of
Pharmacy Research, 4(1), 2011, 136-140.
CONCLUSION
It can be concluded that methyl substitution at terminal
hydroxyl group (ligand 2) and methyl at R6 position (ligand
7) are have better binding interactions with enzyme
Neuraminidase when compared to Zanamivir. The binding
energies of the protein- ligand interactions also confirmed
that the ligands will fit into the active pockets of receptor
tightly. Even by considering the ADME & T profiles,
respective analogs are have better profiles when
compared to other analogs. These may hold better
potential as drug candidates that inhibit the growth of
influenza virus (H1N1). Further development of these
analogs may lead to generation of novel high potent
Neuraminidase inhibitors.
9.
DAISY P, Sasikala R, Ambika A, Analysis of Binding
properties of phosphoinositide 3-kinase through Insilico
molecular docking, Journal of Proteiomics &
Bioinformatics, 2(6), 2009, 274-284.
10.
Egan WJ, Lauri G, Prediction of intestinal permeability,
Advanced Drug Delivery Reviews, 54, 2002, 273–89.
11.
Egan WJ, Merz KM, Baldwin JJ, Prediction of Drug
Absorption Using Multivariate Statistics, Journal of
Medicinal chemistry, 43, 2000, 3867-3877.
12.
Cheng A, Merz K, Prediction of aqueous solubility of a
diverse set of compounds using quantitative structureproperty relationships, Journal of Medicinal Chemistry,
46, 2003, 3572-3580.
13.
Cheng A, Dixon SL, Insilico models for the prediction of
dose-dependent human hepatotoxicity, Journal of
Computer Aided Molecular Design, 17, 2003, 811-823.
14.
Susnow RG, Dixon SL, Use of robust classification
techniques for the prediction of human cytochrome P450
2D6 inhibition, Journal of Chemical Information and
Modeling, 43(4), 2003,1308-1315.
15.
Beigel J, Bray M, Current and future antiviral therapy of
severe seasonal and avian influenza, Antiviral Research,
78, 2008, 91–102.
Dixon SL, Merz KM, One-dimensional molecular
representations and similarity calculations: methodology
and validation, Journal of Medicinal Chemistry, 44(23),
2001, 3795-3809.
16.
PINTO LH, LAMB RA, The M2 Proton Channels of Influenza
A and B Viruses, The Journal of Biological Chemistry, 281,
2006, 8997-9000.
Xia, X, Maliski EG, Gallant P, Rogers D, Classification of
kinase inhibitors using a Bayesian model, journal of
Medicinal Chemistry, 47, 2004,4463-4470.
17.
Rohan, Suranjana Das, Ashley Stanley, Lumbani Yadav,
Akulapalli Sudhakar, Ashok K Varma, Optimized
Hydrophobic Interactions and Hydrogen Bonding at the
Target-Ligand Interface Leads the Pathways of DrugDesigning, PLoS ONE 5(8), 2010, e12029.
18.
Roger SA, Jianhan C, Charles LB, An Evaluation of Explicit
Receptor Flexibility in Molecular Docking Using Molecular
Dynamics and Torsion Angle Molecular Dynamics, Journal
of Chemical Theory and Computation, 5(10), 2009, 2909–
2923.
19.
GUOSHENG WU, DANIEL HR, CHARLES LB, MICHAL V,
Detailed Analysis of Grid-Based Molecular Docking: A Case
Study of CDOCKER—A CHARMm-Based MD Docking
Algorithm, Journal of Computational Chemistry, 24(13),
2003, 1549–1562.
REFERENCES
1.
2.
3.
4.
Brockwell-Staats C, Webster RG, Webby RJ, Diversity of
Influenza Viruses in Swine and the Emergence of a Novel
Human Pandemic Influenza A (H1N1), Influenza and Other
Respiratory Viruses, 3, 2009, 207-213.
Pawan Sharma, Ajay Kumar, Immunoinformatics:
Screening of Potential T Cell Antigenic Determinants in
Proteome of H1N1 Swine Influenza Virus for Virus Epitope
Vaccine Design, Journal of Proteomics & Bioinformatics,
3(9), 2010, 275-278.
5.
Andreas Handel, Ira ML, Rustom Antia, Neuraminidase
Inhibitor Resistance in Influenza: Assessing the Danger of
Its Generation and Spread, PLoS Computational Biolology,
3(12), 2007, e240.
6.
Ralf Wagner, Mikhail Matrosovich, Hans-Dieter Klenk,
Functional balance between haemagglutinin and
neuraminidase in influenza virus infections, Reviews in
Medical Virology 12(3), 2002, 159–166.
7.
Xiaojin Xu, Xueyong Zhu, Raymond AD, James Stevens, Ian
AW, Structural Characterization of the 1918 Influenza
Virus H1N1 Neuraminidase, Journal of Virology, 82(21),
2008, 10493–10501.
8.
Srinivasan P, Sudha A, Shahul Hameed A, Prasanth Kumar
S, Karthikeyan M, Screening of medicinal plant
compounds against NS5B polymerase of hepatitis C virus
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